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Modeling Route Choice of Utilitarian Bikeshare Users from GPS Data

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Modeling Route Choice of Utilitarian Bikeshare Users from GPS Data University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Masters Theses Graduate School 12-2015 Modeling Route Choice of Utilitarian Bikeshare Users from GPS Data Ranjit Khatri University of Tennessee - Knoxville, [email protected] Follow this and additional works at: https://trace.tennessee.edu/utk_gradthes Part of the Transportation Engineering Commons Recommended Citation Khatri, Ranjit, "Modeling Route Choice of Utilitarian Bikeshare Users from GPS Data. " Master's Thesis, University of Tennessee, 2015. https://trace.tennessee.edu/utk_gradthes/3590 This Thesis is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Masters Theses by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. To the Graduate Council: I am submitting herewith a thesis written by Ranjit Khatri entitled "Modeling Route Choice of Utilitarian Bikeshare Users from GPS Data." I have examined the final electronic copy of this thesis for form and content and recommend that it be accepted in partial fulfillment of the requirements for the degree of Master of Science, with a major in Civil Engineering. Christopher R. Cherry, Major Professor We have read this thesis and recommend its acceptance: Shashi S. Nambisan, Lee D. Han Accepted for the Council: Carolyn R. Hodges Vice Provost and Dean of the Graduate School (Original signatures are on file with official studentecor r ds.) Modeling Route Choice of Utilitarian Bikeshare Users from GPS Data A Thesis Presented for the Master of Science Degree The University of Tennessee, Knoxville Ranjit Khatri December 2015 Copyright © 2015 by Ranjit Khatri All rights reserved. ii DEDICATION To My Late Grandfather iii ACKNOWLEDGEMENTS It is a great pleasure to acknowledge my sincere gratitude to my advisor, Dr. Christopher R. Cherry, for his continuous support during my graduate studies and related research. His guidance, motivation, and patience have helped me in all the time of research and writing of this thesis. I would like to thank Dr. Lee D. Han and Dr. Shashi S. Nambisan, who agreed to be a part of my thesis committee. Their insightful comments and encouragement contributed a lot in improving my thesis. I would also like to thank Southeastern Transportation Center (STC), a Federal University Transportation Center, for funding this project and Social Bicycles for providing the GPS data from the Grid Bikeshare – Phoenix, AZ. I am very grateful to my lab mates for the help during my study at The University of Tennessee, Knoxville. They were always willing to help during my study and offer suggestions regarding my future plans. Finally, I would like to thank my family: my parents and my sister for supporting me throughout my life in every good thing I do. iv ABSTRACT This research examines the behavior of bikeshare users from Grid Bikeshare Program in Phoenix, Arizona under two behavioral frameworks: facility usage assessment and route choice assessment. The analysis is performed for the two different categories of subscribers: registered and casual subscribers. This is the first study that uses the real-time GPS data from bikeshare users to model their route preferences. The data used for this study were obtained from 9,101 trips made by 1,866 bikeshare. An important aspect of this bikeshare is that it allows non-station origin and destinations. The GPS points collected from the trips made by bikeshare users were matched to the street base network to determine the attributes of the route followed by the cyclists. Facility usage assessment included the determinations of use of roadway segments based on Annual Average Daily Traffic, posted speed limit, and roadway classification. Similarly, wrong direction riding behavior on the road was compared for one-way versus two-way roads and road segments with bicycle facilities versus without bicycle-facilities. Route choice decisions were modeled using the Path Size Logit model, which is based on a Multinomial Logit framework. The major findings include behavioral differences between the two groups of users such as average distance travelled, time of the day and day of the week variation and composition of the total users. Registered users, although fewer in number, made significant number of trips. Casual users were involved more in wrong direction riding in forty selected road segments from Downtown of Phoenix. The results from the discrete route choice model show that riders were very sensitive to travel distance, with positive utility towards using bike-friendly infrastructure. Having bike- specific infrastructures for the complete route is equivalent to decreasing distance by 44.9% (53.3% for casual users). Left turns imposed higher disutility for casual users as compared to right turns. A number of signalized intersections had a positive effect in selecting the route whereas the proportion of one-way segments, traffic volume and length of the route had a negative influence on route choice. v TABLE OF CONTENTS 1. INTRODUCTION..................................................................................................... 1 1.1. Research Background .................................................................................................... 1 1.2. Research Objectives ....................................................................................................... 2 1.3. Study Area ..................................................................................................................... 3 2. LITERATURE REVIEW ........................................................................................ 4 2.1. Route Choice Criteria Based on Attributes of Traversed Road ..................................... 4 2.2. Impact of Cyclists’ Behavior and Characteristics on Safety .......................................... 5 2.3. New Sources of Bicycle Data: Phone App users and Bikeshare users .......................... 7 2.4. Advantages and Challenges Associated with GPS Data ................................................ 9 3. DATA DESCRIPTION .......................................................................................... 11 3.1. Data Sources ................................................................................................................ 11 3.1.1. Bikeshare GPS Data ................................................................................................ 11 3.1.2. Road Network .......................................................................................................... 12 3.2. Data Cleaning ............................................................................................................... 12 3.3. Completing The Road Network ................................................................................... 14 4. CONCEPTUAL FRAMEWORK AND METHODOLOGY .............................. 15 4.1. Map Matching .............................................................................................................. 15 4.1.1. Available Methods ................................................................................................... 15 4.1.2. Used Procedure ........................................................................................................ 16 4.1.3. Issues and Solutions ................................................................................................. 17 4.2. Choice Set Generation ................................................................................................. 20 4.2.1. Removing the Identical Alternatives ....................................................................... 22 4.2.2. Calculating the Attributes of Alternatives ............................................................... 22 vi 4.3. Discrete Route Choice Model ...................................................................................... 23 4.3.1. Assumptions of Multinomial Logit Model .............................................................. 24 4.3.2. Path Size Logit Model ............................................................................................. 25 4.3.3. Distance Trade-off Calculation ................................................................................ 27 4.4. Variables Utilized in the Model and Hypothesis of Utility .......................................... 27 5. ANALYSIS AND RESULTS ................................................................................. 29 5.1. Demographics of the Bikeshare Users ......................................................................... 29 5.2. The Wrong Direction Riding ....................................................................................... 31 5.3. Facility Usage Assessment ........................................................................................... 34 5.3.1. Distribution of Different AADT Levels or Speed Limits on the Observed Route .. 34 5.3.2. Distribution of Different Roadway Infrastructures on the Observed Route ............ 36 5.4. Route Choice Assessment ............................................................................................ 37 6. DISCUSSION .......................................................................................................... 40 7. CONCLUSIONS, LIMITATIONS, AND FUTURE RESEARCH .................... 45 LIST OF REFERENCES ..............................................................................................
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